Splunk vs Pachyderm

Overview

Splunk

Stacks772

Followers1.0K

Votes20

Pachyderm

Stacks24

Followers95

Votes5

Pachyderm vs Splunk: What are the differences?

Pachyderm: MapReduce without Hadoop. Analyze massive datasets with Docker. Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations; Splunk: Search, monitor, analyze and visualize machine data. It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Pachyderm and Splunk can be categorized as "Big Data" tools.

Some of the features offered by Pachyderm are:

Git-like File System
Dockerized MapReduce
Microservice Architecture

On the other hand, Splunk provides the following key features:

Predict and prevent problems with one unified monitoring experience
Streamline your entire security stack with Splunk as the nerve center
Detect, investigate and diagnose problems easily with end-to-end observability

Pachyderm is an open source tool with 4.35K GitHub stars and 413 GitHub forks. Here's a link to Pachyderm's open source repository on GitHub.

According to the StackShare community, Splunk has a broader approval, being mentioned in 67 company stacks & 170 developers stacks; compared to Pachyderm, which is listed in 5 company stacks and 6 developer stacks.

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Detailed Comparison

Splunk	Pachyderm
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.	Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.
Predict and prevent problems with one unified monitoring experience; Streamline your entire security stack with Splunk as the nerve center; Detect, investigate and diagnose problems easily with end-to-end observability	Git-like File System;Dockerized MapReduce;Microservice Architecture;Deployed with CoreOS
Statistics
Stacks 772	Stacks 24
Followers 1.0K	Followers 95
Votes 20	Votes 5
Pros & Cons
Pros 3 API for searching logs, running reports 3 Alert system based on custom query results 2 Splunk language supports string, date manip, math, etc 2 Query engine supports joining, aggregation, stats, etc 2 Custom log parsing as well as automatic parsing Cons 1 Splunk query language rich so lots to learn	Pros 3 Containers 1 Can run on GCP or AWS 1 Versioning Cons 1 Recently acquired by HPE, uncertain future.
Integrations
No integrations available	Docker Amazon EC2 Google Compute Engine Vagrant

What are some alternatives to Splunk, Pachyderm?

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.